Global business meetings commonly occur by video conference, connecting people across multiple continents and time zones. Video conferences provide attendees with the ability to interact and more clearly communicate using visual and verbal communication cues. Attendees may use facial expressions to aide verbal communication and, through face to face communication, develop relationships that aide in business endeavors and team building.
Sentiment analysis is performed by leveraging natural language processing, text analysis and computational linguistics to identify and extract subjective information in source materials including written or spoken material. Sentiment analysis aides in the understanding of effective communication and recognition of emotions during human-computer interactions. Sentiment analysis includes polarity which considers emotional classifications such as “positive”, “negative” or “neutral” text (or speech) and advanced polarity which considers emotional classifications such as happy, sad, fear, disgust, surprise and anger. A developed and fairly mature technology as applied to the written word such as books, articles, and political event reports, sentiment analysis progresses to the spoken word and human speech with the advent of speech analysis programs and natural language processing. Generally speaking, sentiment analysis aims to determine the attitude and/or reaction of a speaker with respect to some topic or discussion in the overall context of a discussion where the attitude may be determined not just by what is said but, how it is said.
Natural language processing (NLP) is a field of computer science, artificial intelligence, and linguistics. A segment of computer programming that focuses on the interaction between computers and human natural language, NLP creates the ability of a computer to assimilate commands or human speech in natural language and to respond programmatically or to respond verbally (e.g. to reply to a person in a natural language). NLP utilizes linguistics, as one of the building blocks of NLP. Many challenges in NLP involve natural language understanding, that is, enabling computers to derive meaning from human or natural language input. NLP algorithms are based on machine learning, including particularly statistical machine learning.
NLP and sentiment analysis use includes data mining on the internet or social media, product reviews, movie reviews, TV news casts, and chat rooms. Businesses use NLP with sentiment analysis to improve customer relationships, products and company image by increasing an understanding of the customer perceptions and reactions to products and communications such as occurs with live company representatives. Understanding an individual's perceptions or emotional response to written, visual and spoken information and communications provides an opportunity to improve relationships and improve the effectiveness of communication of information for the desired impact.